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A comprehensive county level model to identify factors affecting hospital capacity and predict future hospital demand.
Bhowmik, Tanmoy; Eluru, Naveen.
Afiliação
  • Bhowmik T; Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, USA. tanmoy78@knights.ucf.edu.
  • Eluru N; Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, USA.
Sci Rep ; 11(1): 23098, 2021 11 29.
Article em En | MEDLINE | ID: mdl-34845301
ABSTRACT
The sustained COVID-19 case numbers and the associated hospitalizations have placed a substantial burden on health care ecosystem comprising of hospitals, clinics, doctors and nurses. However, as of today, only a small number of studies have examined detailed hospitalization data from a planning perspective. The current study develops a comprehensive framework for understanding the critical factors associated with county level hospitalization and ICU usage rates across the US employing a host of independent variables. Drawing from the recently released Department of Health and Human Services weekly hospitalization data, we study the overall hospitalization and ICU usage-not only COVID-19 hospitalizations. Developing a framework that examines overall hospitalizations and ICU usage can better reflect the plausible hospital system recovery path to pre-COVID level hospitalization trends. The models are subsequently employed to generate predictions for county level hospitalization and ICU usage rates in the future under several COVID-19 transmission scenarios considering the emergence of new COVID-19 variants and vaccination rates. The exercise allows us to identify vulnerable counties and regions under stress with high hospitalization and ICU rates that can be assisted with remedial measures. Further, the model will allow hospitals to understand evolving displaced non-COVID hospital demand.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article